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Hi,
I am using face-person-detection SSD model, trying to identify both people and faces in security scenarios, when the cameras are typically installed high above. I use the simple image as input, and this model was able to identify faces, but NOT standing people. There are indeed output returned with label == 1, which means this is a person; however, the probability is ~0.1. Why?
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output from this model is:
The net outputs blob with shape: [1, 1, N, 7], where N is the number of detected bounding boxes. For each detection, the description has the format: [image_id
, label
, conf
, x_min
, y_min
, x_max
, y_max
]
image_id
- ID of the image in the batchlabel
- predicted class IDconf
- confidence for the predicted class- (
x_min
,y_min
) - coordinates of the top left bounding box corner - (
x_max
,y_max
) - coordinates of the bottom right bounding box corner.
I was able to detect faces with label == 2. just not people. Thank you for helping out.
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Hi Zhiqi,
Did you resolve your issue by looking in the in-package documentation /opt/intel/computer_vision_sdk/deployment_tools/documentation/docs/face-person-detection-retail-0002.html?
Also, as you can see the pose coverage is standing upright, parallel to image plane so If the camera is to high the accuracy will be poor.
Kind Regards,
Monique Jones
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Hi,
My image is taken at the horizontal position. I found the issue but I don't know how to solve it: the face-person-detection-retail-0002 has two output layers, including detection_out_face and detection_out_pedestrain. So in code, when I use outputInfo.begin()->first, it gives me the layer for face detection. I don't know how to enumerate to the pedestrian output later with outputInfo. I tried the end(), or [], either worked.
Can you please let me know if a model contains several SSD, how can I get through all output layers?
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OK, this is the way to fix it. thanks.
for (auto& output : outputInfo)
{
auto outputName = output.first;
auto& output_ptr = output.second;

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